What I'd Learn Instead of Automation in 2026

[00:01] automation systems, and I'm going to tell you why learning automation in 2026 moves that I think you can make. Uh, before you click off this video, hear me Leftclick. We have worked with everything from local businesses that

[00:13] make 10 grand a month to 8 figureure investment firms and recently a I've also spoken alongside some of the biggest people in business today like Alex Ramosi and Sam Ovens. And to top it off, I run the largest AI community on

[00:25] school by revenue, which just means I get a ton of visibility into how and the way things are going. So, you probably heard some rumblings about that has made all of us a lot of money over the course of the last couple years

[00:38] worthless. I think that there are a select few that are positioning goal with this video is just to add to that select few and then educate people uncomfortable truths for you. AI is advancing very quickly and technical

[00:52] skills are becoming obsolete. But there are a few things that you can learn any automation skill ever could due to leverage. And today I'm going to show you them as well as the exact moment that I personally realized that my big

[01:04] disappearing. And then more importantly what I and and all of you guys could do the video you'll understand why some of the smartest people I know are pivoting something a lot more valuable. Let's do it. So the big lie that everybody in the

[01:17] variant of hey you should learn these tools and you'll be set for life. You naden. You should understand how APIs work. And if you do this magical set of forever. Uh while there are no free lunches in life, I think anybody with a

[01:31] good head on their shoulders can probably sniff the already. The that the technical skills that you're trying to learn today will probably be to fully master them and they get paid for that mastery. And I want to show you

[01:43] exactly why using a framework that's played out in most major industries over before I do, to be clear, it's not that automation is worthless today. It's not you'd be totally screwed or anything. Uh it has a lot of value. I automate stuff

[01:56] businesses routinely. And I get a lot of value out of that. It's just that the implementation of automation is growing less valuable. It is the doing of the thing. Uh because tools are getting better and better every week and they're

[02:09] do a lot of the old technical heavy lifting for you. So, if you followed me basically my main business thesis. I baked it into all of my content. I baked Maker School. I spent the last 6 months or so teaching people business skills

[02:22] weird API call to some deprecated service that barely exists. All I'm saying is that as a whole, eventually we're going to very quickly reach that skill to learn is no longer anywhere near as valuable as just knowing how to

[02:36] skills in the margins get invalidated quickly. And to explain, I want to tell woman that I have just come up with called Sarah the Seamstress. By 1795, Sarah the Seamstress knew 47 different handstitching techniques. She could do

[02:52] French seams and blind hems and decorative embroidery. And all of these very good money because at the time these skills were very rare and valuable. and she had quite the reputation as well until the industrial

[03:05] revolution happened and her skills that were previously rare and valuable were no longer rare and valuable. Okay, fast forward a couple generations. Sarah had didn't need to know those 47 different hand stitching techniques. Instead, what

[03:19] operate a loom, right? Which is like an automated uh stitching machine of the hand stitching techniques, she learned how to maintain and then clean that did what her grandmother did by hand. But now she can do a 100 times

[03:33] faster until the computer revolution happened and then the skills that she previously rare and valuable were no longer rare and valuable. Okay. Anyway, granddaughter, I don't know how many greats we're at now, no longer needs to

[03:46] needs to learn CAD design, which lets her create clothing patterns on a automated manufacturing system that's set up perfectly. Well, what do you great great great granddaughter right now? We're in the AI revolution. So

[04:00] granddaughter doesn't even need to know that cat anymore. All she needs to know is how to prompt AI to generate clothing designs from a simple text description. She literally just needs to know how to say, "Create a summer dress with floral

[04:12] professional settings." And if she's good at that, if she knows how to communicate that to a model, it's done. So the pattern here is that every major skills at the margins of the previous. These are the surface level technical

[04:24] execution skills. These are the stuff that your hands do at the bottom. And at every level, the value in systems moves up. I made this example for you because I'm seeing it all over the internet. Uh in 2020 when I was running 1 second

[04:36] copy, you know, I had to know every make.com module, every API endpoint. All was rare and very difficult to achieve. And so it let me do cool things like scale my own business to over $90,000 in a month in 2025. I don't need to know

[04:49] nan node or make.com module. I don't even need to know most API endpoints business requirements of the person that the documentation of these various use cases then paste them into chat GBT and

[05:04] what is relevant. It's not perfect yet but it will be very shortly. So basically what I'm trying to say is in 2026 and 2027 AI will very clearly be just from the business requirements itself. It'll describe what you want in

[05:18] entire thing which means the value that you bring to an organization. The thing not be your understanding of the tools. It'll not be the stuff that your fingers ability to copy and paste documentation which we are currently doing today in

[05:32] which we are currently doing today in 2025. Instead, future skill will be your suffering from and how to communicate that knowledge to a model so that it can interface between a business and artificial intelligence. Okay. So,

[05:46] start doing. You need to stop memorizing tool features and API documentation. And you need to start understanding business systems and the patterns in value this video. You need to stop learning how to drag and drop modules and start

[06:00] learning how to identify problems worth more than $50,000 or so to solve. The 2026 are not going to be the best at automation tools. In fact, I would go as made money over the even the last couple of years haven't been the best at

[06:13] automation tools, myself included. Uh they will be the best business problem identifiers and they will just happen to use AI as a tool. My second major point that new high lever skill. So, here's what over $100,000 in consulting taught

[06:26] we will become capable of instantiating complete workflows entirely in natural automations. They will be entire business systems. And businesses will this in a clean, straightforward, and logical way. So, my personal timeline on

[06:41] this is that in about 12 months, natural language will create more than 50% of The AI will either build it or it will instantiate one of those agents to take these workflows will still have some issues and highly technical knowledge

[06:54] will be valuable, but it will be valuable in so far that it will allow you to solve AI generated bugs and that's about it. In 24 months, AI will business requirements. That means customer relationship management systems

[07:07] build. Uh inventory tracking systems, sales pipelines, and all of that language prompt. Now, I think it's natural and easy to be scared of this. A knowledge of technical skills and the idea that that knowledge will be

[07:20] value is pretty scary considering my income. But it also creates a massive AI. Right? If you think about it, by moving up a level of abstraction, what level of leverage. And so, you know, it's like an order of magnitude. If

[07:35] right now we're capable of driving X, if you learn the skill up one level of The main upside to AI is that it's very flexible. The main downside to AI is that it is very flexible. So in order to corral all that flexibility into some

[07:48] framework and that is really the skill to learn. So what I'm going to do next prompting. This is developed a couple years ago in a research paper. Uh not a the underlying framework that a lot of high quality prompts and businesses

[08:02] in enterprise. So I'm going to give this to you. You guys can do whatever the some money. It's called the clear framework. C L E A R. The C stands for clarity. The L stands for logic. The E stands for examples. The A stands for

[08:17] results. And I'm going to guide you through what all of that looks like is a precise problem definition with measurable outcomes. You don't want, hey, build me a lead genen system. You want something that's like, create a

[08:29] one-page qualification SOP that identifies companies with 50 plus employees in manufacturing that have also expressed interest in automation extraordinarily clear with what you want. L stands for logic which is

[08:42] follow and execute. Basically where you break down a bunch of complex problems into sequential steps with clear decision points. Then you want examples and edge cases. You know like if there are three or four outcomes you want to

[08:55] delineate and then talk about each. If you're doing your lead qualification points you should route to a senior sales route. Um if it's below 50 points between 50 and 80 schedule a demo call right like make it really clear what the

[09:08] outcomes are. The A for adaptation stands for iterative refinement based on AI feedback. So most people just prompt once. They'll expect perfect results and actually in the conversation going back and forth refining and improving the

[09:21] output based on some sort of eval. And then finally results which are where you business requirements. So can you measure success? Can you prove return on investment? If so, you're doing pretty reasonable. In a year or two, when AI

[09:34] workflows from scratch with very high reliability, your ability to use money you make. Here's an example of a bad prompt that does not follow Clear. here's an example of a good prompt that does follow Clear. Create an outline for

[09:49] It is for a B2B manufacturing consultancy. Incoming leads will come lead qualification system should score them based on company size. If there are 50 plus employees, it is 30 points. If the industry is manufacturing, add 25

[10:04] points. If the engagement level, it's a downloaded white paper, is 20 points. Leads scoring 80 plus should automatically route to a senior sales rep with a Slack notification. Leads scoring 50 to 79 should get scheduled

[10:17] below 50 should enter a sixweek nurturing sequence with industry integrate with HubSpot and track conversion rates at each stage. Right. If you send the first prompt, you'll get a generic template. Since AI is

[10:31] all sorts of different tools that it could use to solve the solution. Uh the consistent. And business pays for consistency. The second constrains that want. So it is very specific, but

[10:44] like a like a bowling lane. It's giving AI the guard rails to act within certain that systems thinking transcends specific skills. So here's why Michael he'd wanted to. It's not because he was naturally gifted at tennis. He'd never

[10:58] played professionally. It's because elite athletes understand one level up. don't just understand the specific techniques. They know the shape of systems and mental preparation and competitive strategy and recovery and so

[11:12] same principle applies to business. A marketing agency and an AI automation agency actually look almost the exact same except for the deliverable. They system. They have the exact same project management. They have almost the exact

[11:26] same team structure. and odds are they have very similar pricing models. If you business, you can make any service business work. Now, this is systems skill you can develop because it transcends whatever specific technology

[11:39] or tool happens to be popular in a given moment. And instead, you focus on wider themes that are shared between them. The specific tactic may change, but the wider strategy never does because the wider strategy of our economy is rooted

[11:51] you what I mean with one of my own businesses. I started with a content agency called 1 second copy, right? We hit 92,000 bucks a month using some very creation workflows. Uh we had a few client management processes. We had a

[12:05] team structure. I had some management skills and so on and so forth. Now when Leftclick, which is our automation agency, I want you to know that the shape of our business was basically the same. Despite the fact that we were

[12:17] which is automation, it turns out that an agency is an agency. Most of the processes in any agency like your lead generation, your sales, your marketing, are going to be the same regardless of whatever thing you're selling. So in our

[12:31] consolidating high-quality agency knowledge. What we did is we just took that higher level strategy, the shape of this container called an agency, and we just poured a bunch of leads into it. And I scaled this to $72,000 in a month.

[12:45] find pretty good success with it so long as you understand the shape of a business. So all you need to learn is the shape of business and you'll be able learn like a specific uh instantiation or technical implementation of a

[12:58] business. Okay. So in general what is a shape of a business? Well here it is. Uh marketing leads to sales which leads to onboarding which leads to delivery which sort of retention. Every business will follow this pattern whether you are

[13:11] selling websites or automations or legal advice or information products or yeah, the main takeaways of this video are our prior skill automation is at the margins, it's getting invalidated pretty quickly. The new higher level skill is

[13:25] models. And the even higher level skill is understanding the flow of value and seeing businesses as a general container, each with their own shapes shape. The unfortunate truth is that automation skills kind of have an

[13:38] we're all learning today will eventually be automated away by AI. And I think a lot of people here probably see that as a very bad thing. Logically, I would eventually added massively to the quality of life of every single

[13:51] generation, and our generation is one of them. It's just hard to see it when the well. You know what I mean? If you guys want to position yourself to win in this video is how you do it. And don't be afraid to change. I'd encourage you

[14:04] If this is what you guys want to do, check out Maker School. We focus overwhelmingly on learning the business behind AI, the shape of this container, biased obviously, but I can't think of any place that is better positioned for

[14:18] link in the bio below if you want that. And if you guys would like help business, if you guys want to see the sorts of things I'm talking about here, forth applied to your company, then I encourage you to work with my team,

[14:31] Just book a call below and we'll set you up. Thanks for watching. Have a lovely rest of the day. I'll catch all y'all in the next video. Bye.